In this paper, we address the problem of estimating the 3D structure and motion of a deformable object given a set of image features tracked automatically throughout a video seque...
Alessio Del Bue, Fabrizio Smeraldi, Lourdes de Aga...
This paper proposes a technique for identifying program properties that indicate errors. The technique generates machine learning models of program properties known to result from...
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Many successful models for predicting attention in a scene involve three main steps: convolution with a set of filters, a center-surround mechanism and spatial pooling to constru...
Naila Murray, Maria Vanrell, Xavier Otazu, C. Alej...
Abstract. Using a scenario of multiple mobile observing platforms (UAVs) measuring weather variables in distributed regions of the Pacific, we are developing algorithms that will ...
Nicholas Roy, Han-Lim Choi, Daniel Gombos, James H...